Setting up Hadoop connection - 7.3

Processing (Integration)

Version
7.3
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Talend Studio
Content
Data Governance > Third-party systems > Processing components (Integration)
Data Quality and Preparation > Third-party systems > Processing components (Integration)
Design and Development > Third-party systems > Processing components (Integration)
Last publication date
2024-02-21

Procedure

  1. Click Run to open its view and then click the Hadoop Configuration tab to display its view for configuring the Hadoop connection for this Job.
  2. From the Property type list, select Built-in. If you have created the connection to be used in Repository, then select Repository and thus the Studio will reuse that set of connection information for this Job.
  3. In the Version area, select the Hadoop distribution to be used and its version.
    • If you use Google Cloud Dataproc, see Google Cloud Dataproc.

    • If you cannot find the Cloudera or Hortonworks version to be used from the Version drop-down list, you can add your distribution via some dynamic distribution settings in the Studio.
      • On the version list of the distributions, some versions are labelled Builtin. These versions were added by Talend via the Dynamic distribution mechanism and delivered with the Studio when the Studio was released. They are certified by Talend, thus officially supported and ready to use.
      If you cannot find the Cloudera version to be used from this drop-down list, you can add your distribution via some dynamic distribution settings in the Studio.
      • On the version list of the distributions, some versions are labelled Builtin. These versions were added by Talend via the Dynamic distribution mechanism and delivered with the Studio when the Studio was released. They are certified by Talend, thus officially supported and ready to use.
    • If you cannot find from the list the distribution corresponding to yours, select Custom so as to connect to a Hadoop distribution not officially supported in the Studio. For a step-by-step example about how to use this Custom option, see Connecting to a custom Hadoop distribution.

  4. In the Name node field, enter the location of the master node, the NameNode, of the distribution to be used. For example, hdfs://tal-qa113.talend.lan:8020.
    • If you are using a MapR distribution, you can simply leave maprfs:/// as it is in this field; then the MapR client will take care of the rest on the fly for creating the connection. The MapR client must be properly installed. For further information about how to set up a MapR client, see the following link in MapR's documentation: http://doc.mapr.com/display/MapR/Setting+Up+the+Client

    • If you are using WebHDFS, the location should be webhdfs://masternode:portnumber; WebHDFS with SSL is not supported yet.

  5. In the Resource Manager field, enter the location of the ResourceManager of your distribution. For example, tal-qa114.talend.lan:8050.
    • Then you can continue to set the following parameters depending on the configuration of the Hadoop cluster to be used (if you leave the check box of a parameter clear, then at runtime, the configuration about this parameter in the Hadoop cluster to be used will be ignored):

      • Select the Set resourcemanager scheduler address check box and enter the Scheduler address in the field that appears.

      • Select the Set jobhistory address check box and enter the location of the JobHistory server of the Hadoop cluster to be used. This allows the metrics information of the current Job to be stored in that JobHistory server.

      • Select the Set staging directory check box and enter this directory defined in your Hadoop cluster for temporary files created by running programs. Typically, this directory can be found under the yarn.app.mapreduce.am.staging-dir property in the configuration files such as yarn-site.xml or mapred-site.xml of your distribution.

      • Select the Use datanode hostname check box to allow the Job to access datanodes via their hostnames. This actually sets the dfs.client.use.datanode.hostname property to true. When connecting to a S3N filesystem, you must select this check box.

  6. If you are accessing the Hadoop cluster running with Kerberos security, select this check box, then, enter the Kerberos principal name for the NameNode in the field displayed. This enables you to use your user name to authenticate against the credentials stored in Kerberos.
    • If this cluster is a MapR cluster of the version 5.0.0 or later, you can set the MapR ticket authentication configuration in addition or as an alternative by following the explanation in Connecting to a security-enabled MapR.

      Keep in mind that this configuration generates a new MapR security ticket for the username defined in the Job in each execution. If you need to reuse an existing ticket issued for the same username, leave both the Force MapR ticket authentication check box and the Use Kerberos authentication check box clear, and then MapR should be able to automatically find that ticket on the fly.

    In addition, since this component performs Map/Reduce computations, you also need to authenticate the related services such as the Job history server and the Resource manager or Jobtracker depending on your distribution in the corresponding field. These principals can be found in the configuration files of your distribution. For example, in a CDH4 distribution, the Resource manager principal is set in the yarn-site.xml file and the Job history principal in the mapred-site.xml file.

    If you need to use a Kerberos keytab file to log in, select Use a keytab to authenticate. A keytab file contains pairs of Kerberos principals and encrypted keys. You need to enter the principal to be used in the Principal field and the access path to the keytab file itself in the Keytab field. This keytab file must be stored in the machine in which your Job actually runs, for example, on a Talend Jobserver.

    Note that the user that executes a keytab-enabled Job is not necessarily the one a principal designates but must have the right to read the keytab file being used. For example, the username you are using to execute a Job is user1 and the principal to be used is guest; in this situation, ensure that user1 has the right to read the keytab file to be used.

  7. In the User name field, enter the login user name for your distribution. If you leave it empty, the user name of the machine hosting the Studio will be used.
  8. In the Temp folder field, enter the path in HDFS to the folder where you store the temporary files generated during Map/Reduce computations.
  9. Leave the default value of the Path separator in server as it is, unless you have changed the separator used by your Hadoop distribution's host machine for its PATH variable or in other words, that separator is not a colon (:). In that situation, you must change this value to the one you are using in that host.
  10. Leave the Clear temporary folder check box selected, unless you want to keep those temporary files.
  11. Leave the Compress intermediate map output to reduce network traffic check box selected, so as to spend shorter time to transfer the mapper task partitions to the multiple reducers.
    However, if the data transfer in the Job is negligible, it is recommended to clear this check box to deactivate the compression step, because this compression consumes extra CPU resources.
  12. If you need to use custom Hadoop properties, complete the Hadoop properties table with the property or properties to be customized. Then at runtime, these changes will override the corresponding default properties used by the Studio for its Hadoop engine.
    For further information about the properties required by Hadoop, see Apache's Hadoop documentation on http://hadoop.apache.org, or the documentation of the Hadoop distribution you need to use.
  13. If the HDFS transparent encryption has been enabled in your cluster, select the Setup HDFS encryption configurations check box and in the HDFS encryption key provider field that is displayed, enter the location of the KMS proxy.

    For further information about the HDFS transparent encryption and its KMS proxy, see Transparent Encryption in HDFS.

  14. You can tune the map and reduce computations by selecting the Set memory check box to set proper memory allocations for the computations to be performed by the Hadoop system.

    The memory parameters to be set are Map (in Mb), Reduce (in Mb) and ApplicationMaster (in Mb). These fields allow you to dynamically allocate memory to the map and the reduce computations and the ApplicationMaster of YARN.

    For further information about the Resource Manager, its scheduler and the ApplicationMaster, see YARN's documentation such as http://hortonworks.com/blog/apache-hadoop-yarn-concepts-and-applications/.

    For further information about how to determine YARN and MapReduce memory configuration settings, see the documentation of the distribution you are using, such as the following link provided by Hortonworks: http://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.0.6.0/bk_installing_manually_book/content/rpm-chap1-11.html.

  15. If you are using Cloudera V5.5+, you can select the Use Cloudera Navigator check box to enable the Cloudera Navigator of your distribution to trace your Job lineage to the component level, including the schema changes between components.

    With this option activated, you need to set the following parameters:

    • Username and Password: this is the credentials you use to connect to your Cloudera Navigator.

    • Cloudera Navigator URL : enter the location of the Cloudera Navigator to be connected to.

    • Cloudera Navigator Metadata URL: enter the location of the Navigator Metadata.

    • Activate the autocommit option: select this check box to make Cloudera Navigator generate the lineage of the current Job at the end of the execution of this Job.

      Since this option actually forces Cloudera Navigator to generate lineages of all its available entities such as HDFS files and directories, Hive queries or Pig scripts, it is not recommended for the production environment because it will slow the Job.

    • Kill the Job if Cloudera Navigator fails: select this check box to stop the execution of the Job when the connection to your Cloudera Navigator fails.

      Otherwise, leave it clear to allow your Job to continue to run.

    • Disable SSL validation: select this check box to make your Job to connect to Cloudera Navigator without the SSL validation process.

      This feature is meant to facilitate the test of your Job but is not recommended to be used in a production cluster.

  16. If you are using Hortonworks Data Platform V2.4.0 onwards and you have installed Atlas in your cluster, you can select the Use Atlas check box to enable Job lineage to the component level, including the schema changes between components.

    With this option activated, you need to set the following parameters:

    • Atlas URL: enter the location of the Atlas to be connected to. It is often http://name_of_your_atlas_node:port

    • Die on error: select this check box to stop the Job execution when Atlas-related issues occur, such as connection issues to Atlas.

      Otherwise, leave it clear to allow your Job to continue to run.

    In the Username and Password fields, enter the authentication information for access to Atlas.